{"id":"https://openalex.org/W4401634900","doi":"https://doi.org/10.1109/tnnls.2024.3426529","title":"High-Precision Dichotomous Image Segmentation With Frequency and Scale Awareness","display_name":"High-Precision Dichotomous Image Segmentation With Frequency and Scale Awareness","publication_year":2024,"publication_date":"2024-08-16","ids":{"openalex":"https://openalex.org/W4401634900","doi":"https://doi.org/10.1109/tnnls.2024.3426529","pmid":"https://pubmed.ncbi.nlm.nih.gov/39150797"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3426529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3426529","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000581688","display_name":"Qiuping Jiang","orcid":"https://orcid.org/0000-0002-6025-9343"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiuping Jiang","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ningbo University, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0002-6025-9343","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112906303","display_name":"Jinguang Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinguang Cheng","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ningbo University, Ningbo, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023784","display_name":"Zongwei Wu","orcid":"https://orcid.org/0000-0001-7772-4152"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zongwei Wu","raw_affiliation_strings":["Computer Vision Laboratory, IFI and CAIDAS, University of Würzburg, Würzburg, Germany"],"raw_orcid":"https://orcid.org/0000-0001-7772-4152","affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, IFI and CAIDAS, University of Würzburg, Würzburg, Germany","institution_ids":["https://openalex.org/I25974101"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091558139","display_name":"Runmin Cong","orcid":"https://orcid.org/0000-0003-0972-4008"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Cong","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0003-0972-4008","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052236177","display_name":"Radu Timofte","orcid":"https://orcid.org/0000-0002-1478-0402"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Radu Timofte","raw_affiliation_strings":["Computer Vision Laboratory, IFI and CAIDAS, University of Würzburg, Würzburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, IFI and CAIDAS, University of Würzburg, Würzburg, Germany","institution_ids":["https://openalex.org/I25974101"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000581688"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":null,"apc_paid":null,"fwci":3.8691,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.9348918,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"36","issue":"5","first_page":"8619","last_page":"8631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.5557000041007996,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.5557000041007996,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.5317999720573425,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.4878000020980835,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.580130934715271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5308495759963989},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.480800062417984},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47873684763908386},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4586096405982971},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43930262327194214},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4163805842399597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36053434014320374},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35320422053337097},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24672791361808777},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.19276347756385803},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19271895289421082}],"concepts":[{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.580130934715271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5308495759963989},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.480800062417984},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47873684763908386},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4586096405982971},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43930262327194214},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4163805842399597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36053434014320374},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35320422053337097},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24672791361808777},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.19276347756385803},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19271895289421082}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3426529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3426529","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:39150797","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39150797","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1436512708","display_name":null,"funder_award_id":"62271277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4447798390","display_name":null,"funder_award_id":"LR22F020002","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G7358290909","display_name":null,"funder_award_id":"2022J081","funder_id":"https://openalex.org/F4320332587","funder_display_name":"Natural Science Foundation of Ningbo"},{"id":"https://openalex.org/G8143921661","display_name":null,"funder_award_id":"LR22F020002","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326189","display_name":"Taishan Scholar Project of Shandong Province","ror":null},{"id":"https://openalex.org/F4320332587","display_name":"Natural Science Foundation of Ningbo","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336656","display_name":"Thousand Young Talents Program of China","ror":null},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1947031653","https://openalex.org/W1974083340","https://openalex.org/W1982075130","https://openalex.org/W1994922096","https://openalex.org/W2039313011","https://openalex.org/W2041719651","https://openalex.org/W2044673646","https://openalex.org/W2047670868","https://openalex.org/W2065985528","https://openalex.org/W2089045143","https://openalex.org/W2100470808","https://openalex.org/W2142771691","https://openalex.org/W2152233525","https://openalex.org/W2161185676","https://openalex.org/W2194775991","https://openalex.org/W2295475768","https://openalex.org/W2493502717","https://openalex.org/W2503331469","https://openalex.org/W2504335775","https://openalex.org/W2545065926","https://openalex.org/W2604469346","https://openalex.org/W2752782242","https://openalex.org/W2788154928","https://openalex.org/W2798857366","https://openalex.org/W2807259068","https://openalex.org/W2807746031","https://openalex.org/W2808442315","https://openalex.org/W2916798096","https://openalex.org/W2919115771","https://openalex.org/W2961348656","https://openalex.org/W2963037989","https://openalex.org/W2963112696","https://openalex.org/W2963150697","https://openalex.org/W2963529609","https://openalex.org/W2963868681","https://openalex.org/W2968748054","https://openalex.org/W2984016939","https://openalex.org/W2995936506","https://openalex.org/W2998449272","https://openalex.org/W3035010169","https://openalex.org/W3092344722","https://openalex.org/W3097053213","https://openalex.org/W3108608656","https://openalex.org/W3116794818","https://openalex.org/W3164098653","https://openalex.org/W3168112135","https://openalex.org/W3171398643","https://openalex.org/W3173632900","https://openalex.org/W3174887243","https://openalex.org/W3175515048","https://openalex.org/W3176152216","https://openalex.org/W3182849571","https://openalex.org/W3185043317","https://openalex.org/W3187910480","https://openalex.org/W3190335749","https://openalex.org/W3197838298","https://openalex.org/W3202263958","https://openalex.org/W3203718853","https://openalex.org/W4224111766","https://openalex.org/W4239147634","https://openalex.org/W4283724275","https://openalex.org/W4283813802","https://openalex.org/W4285310685","https://openalex.org/W4285601297","https://openalex.org/W4292826140","https://openalex.org/W4312265121","https://openalex.org/W4312964941","https://openalex.org/W4313023779","https://openalex.org/W4315490105","https://openalex.org/W4362496243","https://openalex.org/W4362653528","https://openalex.org/W4382450131","https://openalex.org/W4382877880","https://openalex.org/W4385767669","https://openalex.org/W4387211527","https://openalex.org/W4387969113","https://openalex.org/W4387969121","https://openalex.org/W6787967560","https://openalex.org/W6803601828","https://openalex.org/W6849236369","https://openalex.org/W6851839835"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4395685956","https://openalex.org/W2799953226","https://openalex.org/W4398146871","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Dichotomous":[0],"image":[1,11,113],"segmentation":[2,160],"(DIS)":[3],"with":[4,38,183],"rich":[5],"fine-grained":[6],"details":[7],"within":[8],"a":[9,13,70,91,116],"single":[10],"is":[12,36,88,105,129],"challenging":[14],"task.":[15],"Despite":[16],"the":[17,34,39,43,51,55,61,98,109,125,136,142,159,163,167],"plausible":[18],"results":[19,161,190],"achieved":[20],"by":[21],"deep":[22,75],"learning-based":[23],"methods,":[24],"most":[25],"of":[26,84,112,166],"them":[27],"fail":[28],"to":[29,107,131,157],"segment":[30],"generic":[31],"objects":[32],"when":[33],"boundary":[35],"cluttered":[37],"background.":[40],"In":[41,141],"fact,":[42],"gradual":[44],"decrease":[45],"in":[46,100],"feature":[47,138,153],"map":[48],"resolution":[49,134],"during":[50,135],"encoding":[52,139],"stage":[53],"and":[54,73,102,151,178,200],"misleading":[56],"texture":[57],"clue":[58],"may":[59],"be":[60,205],"main":[62],"issues.":[63],"To":[64],"handle":[65],"these":[66],"issues,":[67],"we":[68,145],"devise":[69],"novel":[71],"frequency-":[72],"scale-aware":[74],"neural":[76],"network":[77],"(FSANet)":[78],"for":[79],"high-precision":[80],"DIS.":[81],"The":[82,188,202],"core":[83],"our":[85,180,193],"proposed":[86,181],"FSANet":[87,194],"twofold.":[89],"First,":[90],"multimodality":[92],"fusion":[93,119,149,154],"(MF)":[94],"module":[95,120],"that":[96,192],"integrates":[97],"information":[99],"spatial":[101],"frequency":[103],"domains":[104],"adopted":[106],"enhance":[108],"representation":[110],"capability":[111],"features.":[114],"Second,":[115],"collaborative":[117],"scale":[118],"(CSFM)":[121],"which":[122],"deviates":[123],"from":[124,162],"traditional":[126],"serial":[127],"structures":[128],"introduced":[130],"maintain":[132],"high":[133],"entire":[137],"stage.":[140],"decoder":[143],"side,":[144],"introduce":[146],"hierarchical":[147],"context":[148],"(HCF)":[150],"selective":[152],"(SFF)":[155],"modules":[156],"infer":[158],"output":[164],"features":[165],"CSFM":[168],"module.":[169],"We":[170],"conduct":[171],"extensive":[172],"experiments":[173],"on":[174],"several":[175],"benchmark":[176],"datasets":[177],"compare":[179],"method":[182],"existing":[184],"state-of-the-art":[185],"(SOTA)":[186],"methods.":[187],"experimental":[189],"demonstrate":[191],"achieves":[195],"superior":[196],"performance":[197],"both":[198],"qualitatively":[199],"quantitatively.":[201],"code":[203],"will":[204],"made":[206],"available":[207],"at":[208],"https://github.com/chasecjg/FSANet.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":12}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}